--- task_categories: - text-classification language: - vi --- ## VLSP2018-ABSA-Restaurant ### Dataset Summary The VLSP 2018 Restaurant corpus targets the same ACSA sub-tasks (ACD & SPC) on **4,751** Vietnamese restaurant reviews. This unified CSV includes: * **12** aspect–category indicator columns, each with values {0, 1, 2, 3}. * A `type` column for train/dev/test. * A `dataset` column fixed to `VLSP2018-ABSA-Restaurant`. ### Supported Tasks and Metrics * **Aspect Category Detection** * **Sentiment Polarity Classification** * **Metrics:** Precision, Recall, F1 ### Languages * Vietnamese ### Dataset Structure | Column | Type | Description | | ----------------------------- | ----- | ----------------------------------------------------------------- | | `Review` | `str` | The raw restaurant review. | | `` (12 cols) | `int` | Polarity indicator (0=absent, 1=positive, 2=negative, 3=neutral). | | `type` | `str` | Split: `train` / `validation` / `test`. | | `dataset` | `str` | Always `VLSP2018-ABSA-Restaurant`. | The 12 aspect–category columns: ``` AMBIENCE#GENERAL, DRINKS#PRICES, …, SERVICE#GENERAL ``` ### Usage ```python from datasets import load_dataset ds = load_dataset("visolex/vlsp2018-absa-restaurant") train = ds.filter(lambda ex: ex["type"] == "train") val = ds.filter(lambda ex: ex["type"] == "dev") test = ds.filter(lambda ex: ex["type"] == "test") print(train.features) ``` ### Source & Links * **GitHub:** [https://github.com/ds4v/absa-vlsp-2018](https://github.com/ds4v/absa-vlsp-2018 "https://github.com/ds4v/absa-vlsp-2018") * **Publication:** End-to-end Multi-task Solutions for ACSA on Vietnamese (VLSP 2018) ([github.com][1]) --- ### Citation ```bibtex @INPROCEEDINGS{9865479, author={Dang, Hoang-Quan and Nguyen, Duc-Duy-Anh and Do, Trong-Hop}, booktitle={2022 IEEE International Conference on Cybernetics and Computational Intelligence (CyberneticsCom)}, title={Multi-task Solution for Aspect Category Sentiment Analysis on Vietnamese Datasets}, year={2022}, volume={}, number={}, pages={404-409}, keywords={Sentiment analysis;Analytical models;Computational modeling;Multitasking;Task analysis;Cybernetics;Computational intelligence;Aspect-based Sentiment Analysis;PhoBERT;Aspect Category Detection;Sentiment Polarity Classification}, doi={10.1109/CyberneticsCom55287.2022.9865479}} } ```